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Artificial Intelligence Makes Greener Bike Share Schemes

Since the first coin operated Bike Share Scheme was introduced in Copenhagen in 1995, the health and environmental benefits of Bike Sharing have been widely recognised. If people choose to ride a bike, they aren’t driving a car, riding in a taxi or using mass transit systems. They’re exercising and reducing congestion across a city.

 

That’s all true but we’re seeing that Artificial Intelligence (AI) is able to maximise the positive environmental impact of Bike Share Schemes and make them even more sustainable. Bike Share Schemes that implement an AI platform can push their schemes towards carbon neutrality and demonstrate that they are taking climate change seriously.

 

We have seen it in the schemes that our BICO AI optimisation platform is deployed in. The data shows that AI can directly impact how a Bike Share functions within a city and optimise its operations, reducing CO2 emissions.

 

The biggest impact AI can have is simply getting more people to use a scheme. As mentioned, that means they aren’t using another mode of transport and a city and its citizens are healthier. BICO ensures that users can get the bikes they want where they want them and docks are available at the end of their journey. That makes it convenient to use a Bike Share Scheme and incorporate it into their daily routine.

 

We’ve seen ridership growth across these schemes after they’ve deployed BICO:

 

  • Divvy Bikes, Chicago: Ridership increased by 0.75 Rides Per Day
  • MIBICI, Guadalajara: Ridership increased by 1.5 Rides Per Day
  • City Bikes, Helsinki: Ridership increased by 5 Rides Per Day

 

These numbers are per bike, per day. That’s a huge jump in places like Helsinki, which has a big impact on the benefit the scheme is delivering. This is also combined with more efficient redistribution of bikes across a scheme that translates into a reduced carbon footprint for the schemes operations.

 

Our platform enables the redistribution of bikes to be optimised so that fewer trucks take fewer trips to achieve the best possible results for users.  Over the last year, Bike Share Schemes that use BICO have reduced the amount of time redistribution trucks spend on the road while also cutting the distance they travel by 10,000 miles. That means less CO2 generated by the trucks and a lower carbon footprint for the scheme.

 

BICO is also responsible for 100,000 less bikes needing to be moved, due to the precise and optimal decision making of AI. By streamlining the processes of multiple Bike Share Schemes, we have seen the reduction of up to 10 metric tonnes of CO2 emissions as a direct result of less redistribution trucks being on the road. This has enabled these Bike Share Schemes to take one step closer to their goal of delivering a carbon neutral operation.

 

It all adds up to a clean mode of transport being even cleaner with the use of AI.

 

Let us know if you’d like to learn more about how we support Bike Share Schemes with AI: info@stageintelligence.co.uk

Using Autonomous Vehicles To Manage Bike Share Schemes of the Future

While fully autonomous cars are still years away from being a mode of transportation that we can use day-to-day. We think it could have a positive impact on Bike Share Scheme management in the future.

 

With 68% of the world population projected to live in urban areas by 2050, we believe the future of mobility lies in simpler, cleaner and space saving modes of transportation like walking or cycling. Autonomous cars could play a big part in this.

 

In Bike Share Schemes, driverless cars could open up new opportunities in optimising management to deliver a better scheme to its riders. It can make the redistribution of bikes in the future much easier and more cost-efficient for the operator. Data, Artificial Intelligence (AI) and autonomous technology can all interlink to carry out traditional operational processes.

 

Currently, operators have to rely on manual processes for redistribution with trucks and vehicles being led by operational staff. That requires a significant amount of internal planning on where the drivers need to be, at what time and taking into account shift breaks and patterns.

 

Fortunately, Bike Share operators now have a lot of tools and technology at their fingertips that can help optimise and manage this. AI-based management platforms are helping operators with a lot of the heavy lifting and giving operators the most optimum way to manage operational staff.

 

In a future where driverless cars are commonplace, we can see Bike Share Scheme management moving towards the use of this technology. It has the potential to directly connect with management platforms to optimise how the redistribution trucks move, where they go and how often they go there. That can all be done with minimal human interaction.

 

For Bike Share Scheme operators this can remove the limits on rebalancing its bikes and offer a better and more reliable scheme to its riders. When Bike Share Schemes are better managed, operators can reduce costs and accelerate rider experience.

 

You are able to accurately serve the local market and ensure bikes are available when and where it’s needed. That supports the move towards shared integrated transportation and gets more people cycling.

 

Autonomous cars have a lot of potential for Bike Share Schemes and wider transportation in general, but it is still very far away from reality. At Stage, we’re always looking at the future and seeing how complex challenges of today could be solved by the technologies of tomorrow.

 

We’re excited to see what new technology will bring to the growing shared mobility market and how we can best incorporate it to deliver smarter processes to the wider industry.

 

Please get in touch if you’d like to know more about how we support Bike Share operators with a simplified management processes: tom.nutley(@)stageintelligence.co.uk

 

 

Helsinki AI

Stage Intelligence Deploys Its Artificial Intelligence Platform in Helsinki to Support Bike Share Scheme Growth

Moventia and CityBike Finland OY go live with Artificial Intelligence technology that is simplifying and optimising Helsinki’s Bike Share Scheme.

 

LONDON, 10 July 2018 – Stage Intelligence, the leading provider of Bike Share Scheme management solutions, has partnered with Moventia, a widely recognised urban transport operator, and CityBike Finland OY, the Bike Share operator for Helsinki, to deploy its BICO Artificial Intelligence (AI) platform in Helsinki’s Bike Share Scheme. Helsinki CityBike has gone live with Stage’s AI management platform and is supporting over 600,000 residents with their new season of Bike Sharing.

The BICO solution is actively collecting citywide data and optimising Bike Share operations in Helsinki. The partnership with Stage Intelligence enables CityBike to use its BICO AI platform to drive usability of its more than 2,000 bikes and increase ridership for the new season of Bike Sharing as the CityBike scheme continues to expand into the city of Espoo.

Stage specialises in developing, training and deploying AI technology to optimise the management and operations of Bike Share Schemes globally. Its flagship BICO solution has been helping multiple Bike Share operators around the world deliver a better optimised scheme while reducing operational costs.

“Helsinki is in one of the top ten most livable cities in the world with strong cycling infrastructure and public transportation links. We are excited to go live with CityBike and its partners to transform how over 600,000 Helsinki residents experience Bike Sharing every day. Over 96% of its residents have a positive attitude towards cycling and we’re proud to be using city data and AI to get even more people cycling through optimised and efficient Bike Share Scheme management,” said Tom Nutley, Head of Operations at Stage Intelligence.

BICO is being used to optimise Helsinki’s Bike Share Scheme and get more of its citizens cycling and using public modes of transport. Helsinki is one of the top cities internationally for cycling with around six journeys a day made by bike, according to the City of Helsinki’s Bicycle Account 2017 report. By 2020, it’s aiming to increase the number of journeys taken by bicycle from 10% to 15%.

“Cycling is quite often the fastest and most comfortable way to travel in Helsinki and the city has built quite a strong culture around it. The residents love cycling, and we want to get more people on two wheels and using the city’s extensive public transport methods,” said Jordi Cabañas, GM of the Bikesharing Division at Moventia. We chose Stage Intelligence because they understand the city and have strong processes that can help us achieve our ambitious goals in making Bike Sharing more accessible and attractive to all citizens of Helsinki.”

With population figures expected to reach 860,000 people by 2050, city officials and planners are focused on getting more of its residents cycling. Helsinki City Bikes have been at the heart of promoting the city’s cycling efforts.

“Public transportation is a big part of Helsinki with over 50% of the population relying on it for its daily commuting and Bike Sharing plays a very special role in this. Over 60% of users combine CityBike with public transportation and use it to get around the city as the Bicycle Account report states. It’s why we’ve gone live with Stage Intelligence to deliver a more efficient Bike Share Scheme and help more people in Helsinki see bikes and public transportation as a viable mode of travel,” said Juha Pitkänen, Service Manager at CityBike Finland Oy.

Stage’s BICO solution is currently deployed in numerous Bike Share Schemes around the globe including Divvy Bikes in Chicago, MIBICI in Guadalajara and Helsinki CityBike with several more deployments in the near future. It has been crucial in reducing operational costs for operators and enabling the rapid roll out of new features for its riders. Stage Intelligence has supported the Divvy Bike Share Scheme achieve over 15 million trips in Chicago.

 

About Stage Intelligence

Stage Intelligence specialises in developing Artificial Intelligence solutions for the transport and logistics industry. Its flagship solution, the BICO recommendation engine, delivers real-time intelligence for the management of Bike Share Schemes.

BICO enables precise and optimal decision making and has been purpose-built to remove the complexity from managing resources within a Bike Share Scheme. Partners choose Stage Intelligence because its solutions increase their agility, adaptability and enable them to move beyond traditional manual processes.

Since its inception in 2011, Stage has collaborated with leading Bike Share operators from around the world to solve complex problems and deliver solutions that have a lasting impact on their operations.

www.stageintelligence.co.uk

 

About Moventia

Moventia is a public transport group since 1923, with a clear international vocation. Moventis is specialized in all type of mobility services (regular, urban, interurban and special) and moves around 110 million passengers per year with 1.300 buses, 41 tramways, special services and 26.000 bicycles, both traditional and electric with 1.700 stations. Regarding the automotive industry – 65 years this year – Movento sells about 27.000 new and used vehicles of the 17 brands it represents. Moventia, with 4.000 employees, is defined as a socially responsible group committed with the society, people, institutions and the environment.

www.moventia.com

 

About CityBike Finland OY

CityBike Finland is a subsidiary of Smoove and Moventia. The consortium is responsible for producing and operating the Helsinki Bike Share System. It was awarded a ten-year bicycle contract for the city of Helsinki, which was signed in December 2015 between HKL and the Moventia-Smoove consortium. CityBike Finland has also won an eight-year contract for the Finnish city of Espoo.

The Helsinki Bike Sharing service offers a turnkey solution aimed at providing the citizens of Helsinki with the most advanced public bicycle service in the world via a service with 1,500 bikes and 150 stations.

www.citybikefinland.fi

 

Artificial Intelligence for Modern Transport Operators

With an AI-based management platform, transport operators benefit from utilising a variety of data sources. For Bike Share Schemes, the platform can give insights as to where bikes are required and instantly inform distribution trucks about where bikes need to be picked up and dropped off. When information is being processed instantly and communicated to drivers, there is no lag between new demand emerging and that demand being served.

The value of AI is its ability to process vasts amount of data across a Smart City and make it useful for operators. Citizens get the resources they need and that supports the long-term sustainable growth of public transport.

As a form of modern transport, AI platforms simplify the management of Bike Share Schemes and deliver unique benefits to operators:

 

User Satisfaction

Increased user satisfaction by ensuring bikes and docking points are available when and where required

 

Cost Reductions

Improved operational efficiency and reduced requirement of operational resources

 

Remove Unnecessary Processes

Move away from traditional schedule or dispatch-based approaches and eliminate wasted journeys

 

New Visibility

Real-time truck locations, colour coded station status and station clustering as well as access to advanced analytics and actionable reports via a single dashboard

 

Increased Autonomy

Drivers receive direct communications often via a mobile app, allowing them to work independently of each other and the back office with less wasted time

 

Greater Control

Autonomous operation of a Bike Share Scheme that reflects real time conditions, offers consistent delivery instruction and a detailed overview of the scheme

 

Scenario Simulation

The simulation engine in such management platforms offers the ability to see responses to “what if” scenarios, allowing improved and more efficient resource planning

 

Scale Up

Increase the size of a Bike Share Scheme without the need to simultaneously increase available resource to maintain operation levels

 

The demand for public transport is growing with more citizens turning to Bike Share Schemes as a viable mode of transport. In a growing and competitive Bike Share market, AI could be the key to success for many operators. It has already proven its value to some of the largest schemes in the world and will continue to be at the heart of modern transportation in the future.

 

To find out more about the advantages of utilising AI in transportation read our full whitepaper on ‘How to Grow a Smart City Bike Share Scheme’.

Solving Distribution Challenges in Bike Share Schemes

Effective distribution, in some of the best Bike Share Schemes, require immense amounts of citywide data to be captured, processed and used. Increasingly, schemes around the world are using city data to not only optimise its redistribution but to also show complete visibility to its users as to where the bikes are on its system map.

It’s how Bike Share Schemes use this data that drives value for operators, riders and cities. Bike Share Scheme operators are often familiar with rider statistics and patterns but the challenge is to use this data to accelerate growth within a scheme.

Tracking growth and stimulating growth are often two very different things. At the heart of new growth is rider experience. Bike Share Schemes are challenged to offer a consistent rider experience across a city while ensuring that using a Bike Share Scheme is easy, convenient and enjoyable for the rider. A positive and consistent Bike Share Scheme begins and ends with two questions:

 

  1. “Can I get a bike where I want one?”
  2. “Can I dock my bike at the end of my journey?”

 

If a Bike Share Scheme can guarantee these two things, it is likely that a rider will have a positive riding experience. When a rider can borrow a bike and dock it, they are more likely to use the scheme again and make it part of their routine.

That’s good for the Bike Share Scheme as it will help to grow overall ridership and new people will experience the city using shared bikes. A Bike Share Scheme with an active and growing ridership is able to invest and expand its schemes.

The data available in a city can be used to ensure that riders can access bikes and docks where and when they want them. Different days of the week, weather, events, seasons, local conditions and scenarios, and a whole range of criteria can shape how a Bike Share Scheme is used.

On a rare rainy day in Los Angeles, people may not cycle at all. In Amsterdam, there may only be a slight variance in usage patterns. At the same time, different events can be connected like a sunny day in a city, matched with a train drivers strike and major sporting event being held in one area of the city. All of these factors can influence how a scheme is functioning and where more or less bikes are needed.

Artificial Intelligence (AI) can be an excellent tool for simplifying Bike Share Scheme operations while using the power of data to drive decision making. AI can process a variety of data both historically and in real-time
to deliver actionable insights for Bike Share Scheme operators. Operators gain visibility into all of the criteria shaping a cityscape and benefit from useful insights to optimise bike distribution to match changing conditions.

AI accelerates how decisions are made by operators while taking the guess work out of bike distribution. The AI technology can predict peak times up to 12 hours in advance, enabling operators to manage supply and meet requirements in those areas. This ultimately leads to bikes and docks being available and riders getting a better Bike Share experience.

 

To find out more about the role data and AI has on a Bike Share Scheme, read our full whitepaper on ‘How to Grow a Smart City Bike Share Scheme’